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Transactions of Nonferrous Metals Society of China 2018年第2期28卷 193-219页

作者： mohd.atif wahid Zahid A.KHAN Arshad Noor SIDDIQUEE Department of Mechanical Engineering Jamia Millia Islamia

Friction stir welding（FSW） is a solid-state welding process which is capable of joining materials which are relatively difficult to be welded by fusion welding process. Further, this process is highly energy-efficient and environmental-friendly as compared to the fusion welding. Despite several advantages of FSW over fusion welding, the thermal cycles involved in FSW cause softening in joints generally in heat-treatable aluminum alloys（AAs） due to the dissolution or coarsening of the strengthening precipitates leading to decrease in mechanical properties. Underwater friction stir welding（UFSW） can be a process of choice to overcome these limitations. This process is suitable for alloys that are sensitive to heating during the welding and is widely used for heat-treatable AAs. The purpose of this article is to provide comprehensive literature review on current status and development of UFSW and its importance in comparison to FSW with an aim to discuss and summarize different aspects of UFSW. Specific attention is given to basic principle including material flow, temperature generation, process parameters, microstructure and mechanical properties. From the review, it is concluded that UFSW is an improved method compared with FSW for improving joint strength. Academicians, researchers and practitioners would be benefitted from this article as it compiles significantly important knowledge pertaining to UFSW.

关键词： aluminum friction stir welding fusion welding mechanical properties microstructure underwater friction stir welding

Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 357-384页

作者： mohd Anjum Naoufel Kraiem Hong Min Ashit Kumar Dutta Yousef Ibrahim Daradkeh Department of Computer Engineering Aligarh Muslim UniversityAligarh202002India College of Computer Science King Khalid UniversityAbha61413Saudi Arabia School of Computing Gachon UniversitySeongnam13120Republic of Korea Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of Computer Engineering and Information College of Engineering in Wadi AlddawasirPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning *** applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for *** primary concern of ML applications is the precise selection of flexible image features for pattern detection and region *** of the extracted image features are irrelevant and lead to an increase in computation ***,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image *** process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel *** similarity between the pixels over the various distribution patterns with high indexes is recommended for disease ***,the correlation based on intensity and distribution is analyzed to improve the feature selection ***,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the ***,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of ***,the probability of feature selection,regardless of the textures and medical image patterns,is *** process enhances the performance of ML applications for different medical image *** proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected *** mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.

关键词： Computer vision feature selection machine learning region detection texture analysis image classification medical images

A Review on Integration of IoT as an Approach for Energy Saving in Smart Sustainable Cities

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Journal of Environmental Science and Engineering(A) 2025年第1期14卷 60-71页

作者： mohd Addad Shehadeh Al-Taani Architecture Department Faculty of EngineeringAl al-Bayt UniversityMafraq 25113Jordan

Rapid urbanization has been happening around the world,leading to many challenges and difficulties in infrastructure,communication network,transportation,environmental and organizational *** and responsible management of urban resources plays a significant role in sustainable *** sustainable cities use ICTs(Information and Communication Technologies)to improve quality of life,efficiency of urban operation and *** latest advancement in communication,technology,data management,and IoT(Internet of Things)provide a tremendous role for practical implementations and adoption of devices and *** sustainable cities can be intellectualized as an innovative approach of controlling urban resources and valuable components based on the latest advancement in *** study focuses on reviewing and discussing the literature that states the vital components of IoT associated with smart sustainable cities in general and specifically with green energy.

关键词： IOT devices and sensors smart sustainable cities and green energy.

Mechanical characteristics of oil palm fiber reinforced thermoplastics as filament for fused deposition modeling(FDM)

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Advances in Manufacturing 2020年第1期8卷 72-81页

作者： mohd Nazri Ahmad Mohammad Khalid wahid Nurul Ain Maidin mohd Hidayat Ab Rahman mohd Hairizal Osman Izzati Fatin Alis@Elias Faculty of Mechanical and Manufacturing Engineering Technology Universiti Teknikal Malaysia Melaka.Hang Tuah JayaDurian Tunggal 76100MelakaMalaysia Centre for Smart System and Innovative Design Universiti Teknikal Malaysia MelakaHang Tuah JayaDurian Tunggal 76100MelakaMalaysia

Fibers are increasingly in demand for a wide range of polymer composite *** study^purpose was the development of oil palm fiber(OPF)mixed with the thermoplastic material acrylonitrile butadiene styrene(ABS)as a composite filament for fused deposition modeling(FDM).The mechanical properties of this composite filament were then *** is a fiber extracted from empty fruit bunches,which has proved to be an excellent raw material for *** cellulose content of OPF is 43%-65%,and the lignin content is 13%-25%.The composite lilament consists of OPF(5%,mass fraction)in the ABS *** fabrication procedure included alkalinizing,drying,and crushing the OPF to develop the *** OPF/ABS materials were prepared and completely blended to acquire a mix of 250 g of the material for the ***,the FLD25 filament extrusion machine was used to form the OPF/ABS composite into a *** composite filament then was used in an FDM-based 3D printer to print the ***,the printed specimens were tested for mechanical properties such as tensile and flexural *** results show that the presence of OPF had increased the tensile strength and modulus elasticity by approximately 1.9%and 1.05%,***,the flexural strength of the OPF/ABS composite had decreased by 90.6%compared with the virgin ***,the most significant outcome of the OPF/ABS composite was its suitability for printing using the FDM method.

关键词： Natural fibers Oil palm fiber(OPF) Fused deposition modeling(FDM) 3D printer Composite filament

Adaptable and Dynamic Access Control Decision-Enforcement Approach Based on Multilayer Hybrid Deep Learning Techniques in BYOD Environment

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Computers, Materials & Continua 2024年第9期80卷 4663-4686页

作者： Aljuaid Turkea Ayedh M Ainuddin wahid Abdul Wahab mohd Yamani Idna Idris Faculty of Computer Science and Information Technology Universiti MalayaKuala Lumpur50603Malaysia Faculty of Computer Science and Information Technology Shaqra UniversityShaqra11961Saudi Arabia Center for Mobile Cloud Computing Faculty of Computer Science and Information TechnologyUniversiti MalayaKuala Lumpur50603Malaysia

Organizations are adopting the Bring Your Own Device(BYOD)concept to enhance productivity and reduce ***,this trend introduces security challenges,such as unauthorized *** access control systems,such as Attribute-Based Access Control(ABAC)and Role-Based Access Control(RBAC),are limited in their ability to enforce access decisions due to the variability and dynamism of attributes related to users and *** paper proposes a method for enforcing access decisions that is adaptable and dynamic,based on multilayer hybrid deep learning techniques,particularly the Tabular Deep Neural Network Tabular DNN *** technique transforms all input attributes in an access request into a binary classification(allow or deny)using multiple layers,ensuring accurate and efficient access *** proposed solution was evaluated using the Kaggle Amazon access control policy dataset and demonstrated its effectiveness by achieving a 94%accuracy ***,the proposed solution enhances the implementation of access decisions based on a variety of resource and user attributes while ensuring privacy through indirect communication with the Policy Administration Point(PAP).This solution significantly improves the flexibility of access control systems,making themmore dynamic and adaptable to the evolving needs ofmodern ***,it offers a scalable approach to manage the complexities associated with the BYOD environment,providing a robust framework for secure and efficient access management.

关键词： BYOD security access control access control decision-enforcement deep learning neural network techniques TabularDNN multilayer dynamic adaptable flexibility bottlenecks performance policy conflict

Quality of Service Aware Cluster Routing in Vehicular Ad Hoc Networks

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Computers, Materials & Continua 2021年第6期67卷 3949-3965页

作者： Ishtiaq wahid Fasee Ullah Masood Ahmad atif Khan M.Irfan Uddin Abdullah Alharbi Wael Alosaimi Department of Computer Science Abdul Wali Khan University MardanMardan23200Pakistan Department of Computer and Information Technology Sarhad University of Science and Information TechnologyPeshawar25000Pakistan Department of Computer Science Islamia College PeshawarPeshawar25000Pakistan Institute of Computing Kohat University of Science and TechnologyKohat2600Pakistan Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

In vehicular ad hoc networks(VANETs),the topology information(TI)is updated frequently due to vehicle *** frequent changes in topology increase the topology maintenance *** reduce the control message overhead,cluster-based routing schemes are *** clusterbased routing schemes,the nodes are divided into different virtual groups,and each group(logical node)is considered a *** topology changes are accommodated within each cluster,and broadcasting TI to the whole VANET is not *** cluster head(CH)is responsible for managing the communication of a node with other nodes outside the ***,transmitting real-time data via a CH may cause delays in *** real-time data require quick service and should be routed through the shortest path when the quality of service(QoS)is *** paper proposes a hybrid scheme which transmits time-critical data through the QoS shortest path and normal data through *** this way,the real-time data are delivered efciently to the destination on ***,the routine data are transmitted through CHs to reduce the topology maintenance *** work is validated through a series of simulations,and results show that the proposed scheme outperforms existing algorithms in terms of topology maintenance overhead,QoS and real-time and routine packet transmission.

关键词： QoS VANETs routing real-time communication IoT

Characterization of Nitrogen Uptake Pattern in Malaysian Rice MR219 at Different Growth Stages Using ^(15)N Isotope

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Rice science 2015年第5期22卷 250-254页

作者： Mohammad Mu'az HASHIM mohd Khanif YUSOP Radziah OTHMAN Samsuri Abdul wahid Department of Land Management Faculty of Agriculture University Putra Malaysia

Nitrogen （N） use efficiency is usually less than 50%, and it remains a major problem in rice cultivation. Controlled release fertilizer （CRF） technology is one of the well-known efforts to overcome this problem. The efficiency of CRF, however, is very much dependent on the timing of nutrient release. This study was conducted to determine the precise time of N uptake by rice as a guideline to develop efficient CRF. Fertilizer N uptake by rice at different growth stages was investigated by using 15N isotopic technique. Rice was planted in pots, with 15N urea as N source at the rate of 120 kg/hm2. Potassium and phosphorus were applied at the same rate of 50 kg/hm2. Standard agronomic practices were employed throughout the growing periods. Rice plants were harvested every two weeks until maturation at the 14th week and analyzed for total N and 15N content. Nitrogen derived from fertilizer was calculated. Total N uptake in plants consistently increased until the 11th week. After that, it started to plateau and finally declined. Moreover, N utilization by rice plants peaked at 50%, which occurred during the 11th week after transplanting. N derived from fertilizer in rice plants were in the range of 18.7% to 40.0% in all plant tissues. The remaining N was derived from soil. Based on this study, N release from CRF should complete by the 11th week after planting to ensure the maximum fertilizer N uptake by rice plants. Efficient CRF should contribute to higher N derived from fertilizer which also resulted in a higher total N uptake by rice plants, increasing the potential of rice to produce higher yield while at the same time of reducina loss.

关键词： nitrogen use efficienc rice controlled release fertilizer 15N isotope

Systematic Geometric Error Modeling for Workspace Volumetric Calibration of a 5-axis Turbine Blade Grinding Machine

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Chinese Journal of Aeronautics 2010年第5期23卷 604-615页

作者： Abdul wahid Khan School of Mechanical Engineering and Automation Beijing University of Aeronautics and Astronautics

A systematic geometric model has been presented for calibration of a newly designed 5-axis turbine blade grinding machine. This machine is designed to serve a specific purpose to attain high accuracy and high efficiency grinding of turbine blades by eliminating the hand grinding process. Although its topology is RPPPR （P： prismatic; R： rotary）, its design is quite distinct from the competitive machine tools. As error quantification is the only way to investigate, maintain and improve its accuracy, calibra- tion is recommended for its performance assessment and acceptance testing. Systematic geometric error modeling technique is implemented and 52 position dependent and position independent errors are identified while considering the machine as five rigid bodies by eliminating the set-up errors of workpiece and cutting tool. 39 of them are found to have influential errors and are accommodated for finding the resultant effect between the cutting tool and the workpiece in workspace volume. Rigid body kinematics techniques and homogenous transformation matrices are used for error synthesis.

关键词： 5-axis machine tools calibration modeling geometric errors kinematics homogenous transformation matrices

Composition of carbohydrates, surfactants, major elements and anions in PM2.5 during the 2013 Southeast Asia high pollution episode in Malaysia

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Particuology 2018年第2期16卷 119-126页

作者： Shoffian Amin Jaafar mohd Talib Latif Intan Suraya Razak Nurul Bahiyah Abd wahid Md Firoz Khan Thunwadee Srithawirat School of Environmental and Natural Resource Sciences Faculty of Science and Technology Universiti Kebangsaan Malaysia 43600 Bangi Selangor Malaysia Institute for Environment and Development (Lestari) Universiti Kebangsaan Malaysia 43600 Bangi Selangor Malaysia Department of Biology Faculty of Science and Mathematics Universiti Pendidikan Sultan ldris 35900 Tanjung Malim Perak Malaysia Centre for Tropical Climate Change System (IKLIM) Institute of Climate Change Universiti Kebangsaan Malaysia 43600 Bangi Selangor Malaysia Department of Environmental Science Faculty of Science and Technology Pibulsongkram Rajabhat University Phitsanulok Thailand

Haze episodes have become a major concern in Malaysia over the past few decades and have an increasingly important impact on the country each and every year. During haze episodes from biomass burning in Southeast Asia, particularly from Sumatra, Indonesia, particulate matter PM2.5 is found to be one of the dangerous sources of airborne pollution and is known to seriously affect human health. This study determines the composition of carbohydrates （as levoglucosan）, surfactants, major elements, and anions in PM2.5 during a 2013 haze episode. PM2.5 samples were collected from Universiti Kebangsaan Malaysia, Bangi, using a high volume sampler during a seven-day monitoring campaign during the peak of that year＇s haze episode. PM2.5 concentrations ranged between 14.52 and 160.93 μg/m3, exceeding the 2005 WHO air quality guidelines for PM2.5 （25 μg/m3 for 24-h mean）. The patterns for levoglucosan, surfactants, major elements, and anionic compositions were proportional to the PM2.5 concentrations. Changes in PM2.5 observed on days 3 and 4 were influenced by a combination of meteorological factors, which substantiate the theory that such factors play a pivotal role in haze episodes.

关键词： Aerosol Biomass burning Levoglucosan Surfactant Haze Inorganic composition

Adaptation of Vehicular Ad hoc Network Clustering Protocol for Smart Transportation

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Computers, Materials & Continua 2021年第5期67卷 1353-1368页

作者： Masood Ahmad Abdul Hameed Fasee Ullah Ishtiaq wahid atif Khan M.Irfan Uddin Shaq Ahmad Ahmed M.El-Sherbeeny Department of Computer Science Abdul Wali Khan University Mardan23200Pakistan Department of Computing and Technology Iqra UniversityIslamabadPakistan Department of Computer Science and Information Technology Sarhad University of Science and Information TechnologyPeshawar25000Pakistan Department of Computer Science Islamia College PeshawarPeshawar25000Pakistan Institute of Computing Kohat University of Science and TechnologyKohat2600Pakistan Department of Industrial Engineering College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

Clustering algorithms optimization can minimize topology maintenance overhead in large scale vehicular Ad hoc networks(VANETs)for smart transportation that results from dynamic topology,limited resources and noncentralized *** performance of a clustering algorithm varies with the underlying mobility model to address the topology maintenance overhead issue in VANETs for smart *** design a robust clustering algorithm,careful attention must be paid to components like mobility models and performance objectives.A clustering algorithm may not perform well with every mobility ***,we propose a supervisory protocol(SP)that observes the mobility pattern of vehicles and identies the realistic Mobility model through microscopic *** analytical model can be used to determine an efcient clustering algorithm for a specic mobility model(MM).SP selects the best clustering scheme according to the mobility model and guarantees a consistent performance throughout VANET *** simulation has performed in three parts that is the central part simulation for setting up the clustering environment,In the second part the clustering algorithms are tested for efciency in a constrained atmosphere for some time and the third part represents the proposed *** simulation results show that the proposed scheme outperforms clustering algorithms such as honey bee algorithm-based clustering and memetic clustering in terms of cluster count,re-afliation rate,control overhead and cluster lifetime.

关键词： Cluster VANET smart transportation supervisory protocol mobility models